Publications by Dario Floreano

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The output of reverse engineering methods for biological networks is often not a single network prediction, but an ensemble of networks that are consistent with the experimentally measured data. In this paper, we consider the problem of combining the infor ...

Animal locomotion results from a combination of power modulation and cyclic appendage trajectories, but combining these two properties in small-sized robots is difficult. Here, we introduce and characterize a new elastic actuation system based on an invert ...

We describe a new experimental approach whereby an indoor flying robot evolves the ability to navigate in a textured room using only visual information and neuromorphic control. The architecture of a spiking neural circuit, which is connected to the vision system and to the motors, is genetically encoded and evolved on the physical robot without human intervention. The flying robot consists of a small wireless airship equipped with a linear camera and a set of sensors used to measure its performance. Evolve

Vision-based drone swarms have recently emerged as a promising alternative to address the fault-tolerance and flexibility limitations of centralized and communication-based aerial collective systems. Although most vision-based control algorithms rely on th ...

Recent work suggests that jumping locomotion in combination with a gliding phase can be used as an effective mobility principle in robotics. Compared to pure jumping without a gliding phase, the potential benefits of hybrid jump-gliding locomotion includes ...

We describe a model and implementation of evolutionary spiking neurons for embedded microcontrollers with few bytes of memory and very low power consumption. The approach is tested with an autonomous microrobot of less than 1 in^3 that evolves the ability to move in a small maze without human intervention and external computers. Considering the very large diffusion, small size, and low cost of embedded microcontrollers, the approach described here could find its way in several intelligent devices with senso

We aim at developing autonomous micro-flyers capable of navigating within houses or small indoor environments using vision as principal source of information. Due to severe weight and energy constraints, inspiration is taken from the fly for the selection ...

To escape danger or catch prey, running vertebrates rely on dynamic gaits with minimal ground contact. By contrast, most insects use a tripod gait that maintains at least three legs on the ground at any given time. One prevailing hypothesis for this differ ...

In social insects, workers perform a multitude of tasks such as foraging, nest construction and brood rearing without central control of how work is allocated among individuals. It has been suggested that workers choose a task by responding to stimuli gath ...

Robots capable of hover flight in constrained indoor environments have many applications, however their range is constrained by the high energetic cost of airborne locomotion. Perching allows flying robots to scan their environment without the need to rema ...

Unlike existing aerial swarm systems, we aim at developing algorithms which do not require global or relative positioning information concerning agents and their neighbors. This alleviates the need for sensors which require calibration, are expensive and heavy or unusable because of environmental constraints. Rather than positioning, MAVs rely only on simple sensors (magnetic compass, speed sensor and altitude sensor) and local communication with neighbors. Our endeavor is motivated by an application whereb

We aim at implementing a swarm of Micro-Air-Vehicles for creating communication networks (SMAVNETs) in disaster areas. For this purpose, we propose strategies for steering flying robots using only communication hardware (e.g. WiFi module or radio modem) an ...

Biological neural networks continuously adapt and modify themselves in response to experiences throughout their lifetime—a capability largely absent in artificial neural networks. Hebbian plasticity offers a promising path toward rapid adaptation in changing environments. Here, we introduce Hebbian Attractor Networks (HAN), a class of plastic neural networks in which local weight update normalization induces emergent attractor dynamics. Unlike prior approaches, HANs employ dual-timescale plasticity and temp

This paper describes a new kind of genetic representation called analog genetic encoding (AGE). The representation is aimed at the evolutionary synthesis and reverse engineering of circuits and networks such as analog electronic circuits, neural networks, ...

The performance of evolutionary algorithms can be heavily undermined when constraints limit the feasible areas of the search space. For instance, while Covariance Matrix Adapta- tion Evolution Strategy is one of the most efficient algorithms for unconstrai ...

Distinguishing subpopulations in group behavioral experiments can reveal the impact of differences in genetic, pharmacological and life-histories on social interactions and decision-making. Here we describe Fluorescence Behavioral Imaging (FBI), a toolkit ...

Evolutionary algorithms were proposed to automatically find solutions to computational problems, much like evolution discovers new adaptive traits. Lately, they have been used to address challenging questions about the evolution of modularity, the genetic ...

Co-evolution of competitive species provides an interesting testbed to study the role of adaptive behavior because it provides unpredictable and dynamic environments. In this paper we experimentally investigate some arguments for the co-evolution of different adaptive protean behaviors in competing species of predators and preys. Both species are implemented as simulated mobile robots (Kheperas) with infrared proximity sensors, but the predator has an additional vision module whereas the prey has a maximum

We describe a set of simulations to evolve omnidirectional active vision, an artificial retina scanning over images taken via an omnidirectional camera, being applied to a car driving task. While the retina can immediately access features in any direction, ...

Human-Robot Interfaces (HRIs) can be hard to master for inexperienced users, making the teleoperation of mobile robots a difficult task. The development of Body-Machine Interfaces (BoMIs) represents a promising approach to making a user more proficient, by ...

Dario Floreano

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Combining Multiple Results of a Reverse Engineering Algorithm: Application to the DREAM Five Gene Network Challenge

Elastic-Actuation Mechanism for Repetitive Hopping Based on Power Modulation and Cyclic Trajectory Generation

Evolving Vision-based Flying Robots

On the Scalability of Vision-based Drone Swarms in the Presence of Occlusions

Performance analysis of jump-gliding locomotion for miniature robotics

Evolutionary Bits'n'Spikes

Fly-inspired Visual Steering of an Ultralight Indoor Aircraft

Climbing favours the tripod gait over alternative faster insect gaits

Neural networks as mechanisms to regulate division of labor

A Perching Mechanism for Flying Robots Using a Fibre-Based Adhesive

Pheromone-based Swarming for Position-less MAVs

Communication-based Swarming for Flying Robots

Hebbian Attractor Networks for Robot Locomotion

Analog Genetic Encoding for the Evolution of Circuits and Networks

Memetic Viability Evolution for Constrained Optimization

Fluorescence Behavioral Imaging (FBI) tracks identity in heterogeneous groups of Drosophila

Differences in the Concept of Fitness Between Artificial Evolution and Natural Selection

Adaptive Behavior in Competitive Co-Evolutionary Robotics

Omnidirectional Active Vision for Evolutionary Car Driving

Personalized Telerobotics by Fast Machine Learning of Body-Machine Interfaces